Spectrometric techniques have been applied to monitoring mixing processes, such as the mixing of pharmaceutical blends. One approach has been to take a series of single spectra of a blend through a window in a mixing vessel. Mixing can then be carried out until this single measurement reaches an end point. This method is simple to implement, but it provides the user with relatively little information about the distribution of components of the mixture.
Another approach has been to acquire a series of near-infrared chemical images of a blend in a mixing vessel. These images can then be analyzed to derive statistical properties, such as the mean, standard deviation, kurtosis, or skew of the distribution, as described in more detail in published U.S. application No. US2004-0211861, which is herein incorporated by reference. This approach can provide more information about the distribution of mixture components than does the single-measurement approach, but it can be relatively expensive to implement.